1.1 Technical Field
The invention relates to financial systems for estimating the cost of a trade. More particularly, the present invention adds value to the trading process by allowing portfolio managers to estimate the cost of trading and thus make better informed decisions regarding whether and what to trade. Traders should find the present invention useful in helping them decide how to trade a portfolio of stocks and in evaluating a trade after the fact.
1.2 Conventional Art
“Buy low, sell high” has been the mantra of financial traders. In general, traders attempt to buy stocks at a low price then sell at a higher price. However, a time delay often exists between deciding to buy a stock and the execution of the trade. For example, if at the close of a market a stock is priced at $50 a share and a trader decides to purchase the stock, the next opportunity for a trader to purchase the stock is the next morning when the markets open.
This time delay may affect the stock price to the benefit or detriment of the trader. For example, the purchase price to the trader may have increased to $50.50, meaning the trader receives less stock for his investment. In the long run, the trader may pay more at the stock's opening than at the previous night's close. This added cost or friction creates a drag on stock performance.
Other costs associated with trading include fixed costs (which may include fees, taxes, and commissions) and execution costs (which may include spread costs and the impact trade size has on the market). The fixed costs are generally known more or less exactly prior to the trade. The execution costs are determined only when the trade is executed. Because they are not known in advance, execution costs must be estimated. Execution costs can be understood as a combination of spread cost and size impact costs, both of which must be evaluated to estimate execution costs.
Spread costs reflect the cost per share of executing a small order. If one always bought on the offer and sold on the bid, the spread cost would be half the bid-ask spread. However, the spread cost is generally less than half the quoted spread. There are two reasons for this. First, a dedicated trading team can frequently do better than the quoted inside market through the judicious use of limit orders. A second reason is that on certain exchanges (for example the New York Stock Exchange), it is common for market orders to be filled better than the quoted inside market.
Size impact reflects the additional cost per share of trading large orders. The quoted size on the inside bid or ask is frequently small compared with a typical institutional order. In some circumstances, the bid or offer is often good for more shares than the officially quoted size, but may be too small for a larger order. Thus, to execute a larger order, one may have to accept prices outside the current market, leading to an average execution cost that is more than half the bid-ask spread. Furthermore, even for orders that are smaller than the quoted size, one might not have the same ability to execute within the spread that one has for the smallest orders.
In addition, the cost associated with incomplete execution of a transaction may affect a trader's cost. For example, in the course of buying stock, the stock's price may increase to such an extent that it becomes undesirable to buy the remaining shares of the original order. Thus, when estimating the costs of a trade, one should consider the cost associated with the unexecuted purchase and include the opportunity cost of not being able to trade. Otherwise, one will tend to understate the true cost of trading.
Others have attempted to estimate execution costs. Usually, it is measured as the slippage of the execution from some benchmark, measured either in currency units or basis points. Commonly used benchmarks include:                1. The price of the stock just before the trade (often the prior close or closing mid-market is used as a proxy);        2. The volume-weighted average price (VWAP) of the stock over the trading period (sometimes the average of open, high, low and close is used as a proxy); or        3. The price of the stock on the close of trading.        
The first benchmark mentioned above experiences slippage by the so-called “implementation shortfall.” Coined as a term by A. F. Perold in “The Implementation Shortfall: Paper vs. Reality”, The Journal of Portfolio Management, 14 (3) Spring (1988), pages 4–9, the implementation shortfall is the slippage of the execution from the prevailing price before the trade. This is the measure of execution cost that the present system seeks to predict. A virtue of using the price of the stock before the trade begins is that this benchmark cannot be influenced by one's own trading activity. From the portfolio manager's point of view, the implementation shortfall is the difference between his or her actual results and those of paper trading. A disadvantage of this approach is that a stock can move significantly over the trading period independent of one's own trading activity, making it difficult to isolate one's own impact. This can be mitigated somewhat by adjusting for market moves (except for very large programs that may materially move the market). In summary, implementation shortfall is an unbiased but noisy measure of execution cost.
The second benchmark experiences slippage to the volume-weighted average price (VWAP). VWAP is much less noisy than implementation shortfall. If the order is a small percentage of the traded volume, this is a good measure of execution cost. However, VWAP may be materially affected by large orders, understating the cost. For this reason, this measure is of dubious utility for larger orders—precisely the focus of institutional interest.
The third benchmark experiences slippage to the close of trading. The closing price may make sense in situations in which the customer is benchmarked to the close. The close may be affected by the execution of the trade itself.
Various elements contribute to the difficulties in estimating execution costs. First, execution costs are highly volatile. It is not uncommon to experience a negative shortfall or a shortfall of double the typical amount. In the long run and over the course of numerous trades, this volatility tends to cancel itself out somewhat, but it is important to bear it in mind when considering the cost of an isolated trade. Second, there can be considerable variation among managers. The alpha characteristics (the ability to pick good stocks consistently) and trading style of an individual manager can lead to a systematic bias toward a higher or lower implementation shortfall compared with other managers for similar stocks. For example, a manager who is an excellent short-term stock picker will likely experience a high average shortfall, because the stocks he or she buys tend to increase in price regardless of his or her trading activity. In such situations, pre-trade estimates of shortfall may be most useful in determining the relative execution costs for different portfolios or stocks, rather than the absolute level.
Others have attempted to represent costs of trading. These include Plexus Corp., Donaldson, Lufkin & Jenrette, Inc., Salomon Smith Barney Inc., and Barra Inc. However, for various reasons, these other approaches fail to account for various inaccuracies in their approach to estimating execution costs.
Until now, no system has existed that evaluates the above factors and permits a trader to accurately estimate the executing costs of his trades prior to trading.